双能量CT线性融合优化对比技术对肝脏增强图像质量的影响

唐永强,李剑,王栋,石明国

第四军医大学西京医院 放射科,陕西西安 710032

[摘 要]目的 探讨双能量CT线性融合优化对比技术对肝脏增强图像质量影响,获得线性融合方式在肝脏图像质量应用中最佳加权因子。方法 收集50例肝脏双能量CT增强扫描患者线性融合图像数据进行分析测量,比较门静脉期加权因子0.1~0.9融合图像的噪声(SD)、信噪比(Signal to Noise Ratio,SNR)、对比噪声比(Contrast to Noise Ratio,CNR),并对各组图像质量进行主观评分。结果 在加权因子为0.4~0.6的混合能量图像中图像SD较低。加权因子为0.5~0.7时图像的SNR较高,加权因子为0.6~0.8时图像的CNR较高,图像CT值在0.1~0.9加权因子中呈递增趋势。加权因子0.5与0.6、0.6与0.7组SD、SNR、CNR、CT值组间比较无统计学意义,0.5与0.7组组间比较CT值有统计学意义。加权因子0.5、0.6、0.7主观图像质量评价评分较高,0.7组最高,0.6组次之。结论 双能肝脏增强扫描中加权因子为0.6、0.7时均可获取具有相对较低的SD和较高的SNR、CNR、CT值图像,对于观察肝脏乏血供病灶时选择加权因子0.7融合图像最佳,当在肝损害、脂肪肝背景下时,选用较低SD的加权因子0.6时图像观察较佳。

[关键词]双能量CT;线性融合;肝脏增强;图像质量;加权因子

引言

我国肝病患者众多,各种肝病可发展为肝硬化甚至肝癌,肝硬化发病率及死亡率高,严重危害人民群众健康。上腹部CT扫描是疾病诊断一种重要检查方法。双能量CT(Dual Energy CT,DECT)扫描可获取100 kV和140 kV两种单能谱图像,同时经过后处理软件可实现自动去骨技术、双能量肾脏结石分析、痛风结节分析、双能量肺灌注显像及虚拟平扫等[1-4],还可通过线性融合方式(Linear Blending,LB)改善图像质量。现临床应用中常用0.3加权因子线性混合图像非最佳选择[5-7]。本研究探讨双能量CT肝脏增强成像LB不同加权因子对混合图像质量影响,旨在提升双能量成像在肝脏疾病诊断中的应用价值。

1 资料与方法

1.1 一般资料

随机收集50例临床进行肝脏增强的患者双能量CT图像进行分析,其中男32例,女性18例,年龄25~68岁,中位年龄(46.1±2.8)岁。排除标准:碘对比剂过敏患者,体重指数>30 kg/m2,严重心脏疾病,甲状腺功能亢进,孕产妇。

1.2 检查方法及参数

采用西门子双源CT(Def i nition Flash,Siemens Healthare,Forchheim,Gemany)进行检查,扫描参数:140 kV/100 kV,自动毫安控制CAREDose4D扫描模式,准直器2 mm× 64 mm×1.2 mm,螺距0.8,旋转时间0.5 s/圈。动脉期采用自动触发技术检测兴趣区为肝顶腹主动脉,触发阈值为180 HU,动脉期扫描结束后延迟25 s采集门静脉期,门静脉期扫描结束后延迟35 s采集延迟期。对比剂选用优维显(Ultravist 370 mgI/mL,BayerSchering Pharma),经肘前静脉以1 mL/kg,以3.5 mL/s的流速进行注射,注射完对比剂后再以相同的流速注射40 mL生理盐水。

1.3 图像后处理

双能量CT扫描门静脉期以140 kV和100 kV按照0.1~0.9融合图像进行重建(如融合0.1图像为10%的140 kV图像与90%100 kV图像进行融合),将数据传入工作站(Syngo mmwp)进行图像分析和测量。

1.4 图像分析

(1)数据采集:利用Viewing软件将圆形兴趣区分别置于肝左右叶、门静脉主干、腹主动脉、竖脊肌及腹部前方的空气进行测量。记录所测兴趣区的CT值和噪声(即CT值的标准差),每个部位均测量3次,取3次测量的平均值作为最终的CT值和噪声值。测量时尽量选择组织密度较均匀部位,避开肉眼可见的血管、纤维、坏死、囊变或伪影。

信噪比(Signal-to-Noise Ratio,SNR)计算方法为:SNR=兴趣区CT值/SD;对比噪声比(Contrast-to-Noise Ratio,CNR)计算方法为:CNR=(兴趣区CT值-椎旁肌肉CT值)/SD。

测量肝脏左右叶CT值时要求肝脏、门静脉主干、腹主动脉、椎旁肌肉及腹部前方空气的ROI在同一层面,并以后者作为背景噪声。比较不同加权因子混合图像的SD、SNR、CNR。

(2)图像评价:由两名高年资影像诊断医师采用双盲法对SD较低,SNR和CNR较高的几组混合能量图像,固定窗宽、窗位为300 HU和40 HU,观察噪声及对比度,进行图像质量评分。评分标准:一般低为1分;良为2分;优为3分。

1.5 统计学分析

应用SPSS 19.0统计软件进行检验。计量资料采用均值±标准差表示,同一期相不同加权因子的混合能量图像之间采用单因素方差分析,两组间均值的比较采用独立样本t检验,图像质量采用非参数检验,以P<0.05为差异有统计学意义。

2 结果

2.1 双能量CT图像

0.1 ~ 0.9不同加权因子LB图像参数分析结果见表1,图像各参数在9组间总体差异比较有统计学意义。加权因子越大,肝实质CT值越高(图1a),空气SD值在0.4~0.6加权因子中较低(图1b),0.5时最低。CNR值在0.6~0.8加权因子中较高,0.7时最高,SNR值在0.5~0.7加权因子中较高(图1c),0.6时最高。因此选用SD最低0.5组、CNR最高0.7组、SNR最高0.6组加权因子图像进行组间比较。0.5~0.7加权因子(图2)SD、SNR、CNR数据进行两两组间比较,无统计学意义(P>0.05),0.5~0.7加权因子肝左右叶CT值进行进行两两组间比较,0.5与0.6、0.6与0.7组比较无统计学意义,0.5与0.7组比较有统计学意义(P<0.05)。

表1 0.1~0.9加权因子LB图像参数比较

注:SD:噪声;SNR:信噪比;CNR:对比信噪比。

图1 肝脏静脉期不同加权因子参数

2.2 图像质量主观评分比较

0.5 加 权因子混合图像质量评分2分者24例,3分26例;0.6加权因子混合图像质量评分2分者21例,3分29例;0.7加权因子混合图像质量评分2分者20例,3分30例。将0.5加权因子的混合能量图像分别与0.6、0.7组加权因子两组的图像质量评分进行两两比较时,均有统计学意义(P<0.05),0.6与0.7加权因子图像评分对比无统计学意义(P>0.05)。

图2 肝右叶肝癌0.5~0.7加权因子LB图像

注:a.肝右叶肝癌0.5加权因子;b.肝右叶肝癌0.6加权因子;c.肝右叶肝癌0.7加权因子。背景空气SD值分别为5.4、5.6、6.1,肝右叶CT值分别为100.4、103.3、106 HU,SNR值分别为32.13、35.21、36.11,CNR值分别为14.23、16.11、16.96。

3 讨论

随着CT设备不断的更新,推出了更多的检查方法,为临床疾病的诊断带来便利,逐渐使CT检查成为临床疾病诊断中不可或缺的方法。DECT是目前CT成像技术研究领域中的热点之一。DECT成像即在不同的X射线能量照射下,不同成分的组织X线衰减不同,再通过图像融合重组技术得到能体现组织化学成分的CT图像。其图像融合方式分为LB和NLB两类,可取得同时兼具高成像质量与高密度分辨率而低噪声的混合能量图像[8-9],从而改善图像质量,提高临床基本检出率,减少漏诊与误诊。

CT增强扫描技术是肝脏疾病常检查方法,对肝脏疾病检出率及诊断准确率较高,不仅可观察肝内动静脉血管情况,亦可显示肝实质病灶大小、形态、范围及周围结构情况、胆道系统异常等,多种后处理技术可进一步多方位显示肝脏解剖及病变关系。因此提高图像质量对肝脏疾病诊断尤为重要。双能量CT线性融合优化对比技术,一次扫描不仅可获取虚拟平扫图像,尚可获取不同加权因子融合图像,提高图像质量。SD、SNR、CNR是评价图像质量重要参数,SNR、CNR值最为重要,SD值低,SNR、CNR值高时,图像质量最佳。本研究结果显示,0.5加权因子LB图像SD值最低,其图像对比度欠佳,SNR及CNR未达最大值,对于肝脏细小病变易漏诊误诊。当选择SNR最高值为0.6加权因子LB图像,CNR最大值为0.7加权因子LB图像时,SD值适当提高,图像对比度清晰度提高,图像质量良好,肝脏细节情况观察满意,此时肝左右叶CT值相对较高, 两组间对比CT值、SD、SNR、CNR无统计学意义(P>0.05),而0.5与0.7组CT值比较有统计学意义(P<0.05)。因此将0.5~0.7加权因子LB图像进行图像质量评分,对比图像质量评分结果,0.6、0.7加权因子LB图像由于SD值相对低,SNR及CNR高,评分较高,0.7加权因子LB图像评分最高。

目前,线性融合技术在临床应用比较广泛,为图像质量的提高起到积极的作用。其中,Kim等[10]报道显示,加权因子高于0.5的LB图像能提高肝脏的CNR,与研究结果一致。Paul等[11]对40例患者行颈部双能量扫描检查研究结果显示,加权因子为0.6时LB图像SNR及CNR值最大。国内外有文献报道[12-16],肾癌双能量扫描中加权因子为0.6的LB图像具有相对较低的SD和较高的SNR、CNR,与本研究0.6和0.7,研究结论相似,但其在CT值的测量方法及部位选择方面有一定差异性,造成部分结论不同。

综上所述,双能量CT线性融合技术在肝脏增强成像方面具有一定优势,可一次扫描获取虚拟平扫图像,且可利用不同的线性融合加权因子,对肝脏乏血供病灶选择加权因子0.7融合图像最佳,当在肝损害、脂肪肝背景下时,选用较低SD的加权因子0.6图像观察较佳,为诊断提供更多的影像学信息,值得临床推广。

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本文编辑 苏欣

Effect of Linear Blending Optimal Contrast Technique with Dual Energy CT on Liver Image Quality

TANG Yong-qiang, LI Jian, WANG Dong, SHI Ming-Guo

Department of Radiology, Xijing Hospital Aff i liated to the Fourth Medical University, Xi’an Shaanxi 710032, China

Abstract:Objective The objective of this study was to evaluate the effect of linear blending optimal contrast technique using dual-energy CT (DECT) on contrast-enhanced liver images, and acquire an optimal weighting factor. Methods 50 patients undergoing dual energy contrast-enhanced CT of liver were enrolled. For each patient, datasets of linear blended images in the portal phase were generated with weighting factors of 0.1~0.9. Noise (SD), signal to noise ratio (SNR), contrast to noise ratio (CNR), and subjective image quality score of fused images were obtained. Results The noise was lower in fused images with weighting factors of 0.4~0.6. The SNR was higher in fused images with weighting factors of 0.5~0.7. The CNR was higher in fused images with weighting factors of 0.6~0.7. CT value presented an increased tendency with an increase of weighting factors. There were no signif i cant differences in noise, SNR, CNR, or CT value between groups of weighting factors of 0.5 and 0.6, and between groups of weighing factors of 0.6 and 0.7. Noise, SNR, CNR, and CT value were signif i cantly different between groups of weighing factors of 0.5 and 0.7 (P<0.05). Subjective image quality score was the highest in images with weighting factor of 0.7, followed by images with weighting factor of 0.6. Conclusion For linear blended images generated from liver dual energy contrast-enhanced CT scans, images with weighting factors of 0.6 and 0.7 had relatively low noise and high SNR, CNR, and CT value, and images with weighting factors of 0.7 were optimum for observing hypovascular liver lesions. Lower weighting factor of 0.6 was optimal for patients with liver injury or fatty liver.

Key words:dual energy CT; linear blending; enhanced of the liver; image quality; weighting factor

[中图分类号]R581;R816.6

[文献标志码]A

doi:10.3969/j.issn.1674-1633.2017.05.004

[文章编号]1674-1633(2017)05-0015-04

收稿日期:2017-02-11

通讯作者:石明国,教授。

通讯作者邮箱:smg2002@163.com